How LINC Education scales teaching-quality assurance across four continents

About LINC Education

LINC Education is an education services company that partners with universities to deliver high-quality online learning. Their model puts experienced Student Success Tutors alongside university faculty to improve engagement and outcomes in online study modes — across 25+ partner universities on four continents.

The challenge

LINC's quality promise depends on the feedback its tutors write to students. That feedback has to be specific, evidence-based, and consistent — whether the tutor is in Melbourne, Manila, or Dubai, and whether the university's standards are Australian, British, or European.

• It doesn't scale linearly. Every new university partner adds review volume that has to be absorbed by a human QA team.
• Consistency drifts. Different reviewers apply the same rubric differently, and the drift is invisible until a partner complains.
• It's slow where speed matters most. Feedback quality issues are only coachable if the tutor hears about them while the cohort is still running.
• The cost curve is wrong. Growing the partner base meant growing the review team proportionally.

The solution

LINC partnered with PrepareBuddy to run their feedback quality assurance through our RAG-enhanced evaluation engine — not to grade students, but to evaluate the tutors' feedback itself against LINC's own quality rubric.

• Batch evaluation via API and bulk upload — hundreds of feedback entries submitted in one run, evaluated in parallel, returned as structured reports
• LINC's own rubric, not ours — criteria, weightings, performance-level descriptors and band thresholds configured to LINC's standards, with a custom rubric builder they control
• Evidence-anchored scoring — every score cites the tutor's actual words and names the specific gap, so a deduction is defensible and coachable rather than a bare number
• Reference snapshot versioning — each batch stores the exact rubric state, reference set and configuration used, so any evaluation can be reproduced months later during an audit or appeal
• Per-tutor calibration view — agreement rates, strictness bias and recurring mismatch patterns, turning QA output into a coaching input

How it works

1. Upload — LINC submits tutor feedback via batch upload, CSV/Excel, or API
2. Configure — select the rubric and quality standards for that partner or programme
3. Process — the engine evaluates each entry against reference criteria and exemplar material, in parallel
4. Deliver — per-entry reports with scores, evidence citations and improvement recommendations, plus a batch rollup showing band distribution, per-axis averages and per-tutor patterns

The outcome

PrepareBuddy's evaluation engine benchmarks at 94%+ alignment with human markers.

About PrepareBuddy

PrepareBuddy builds AI assessment infrastructure for education. Universities and education providers use our evaluation engine to grade subjective and handwritten work against their own rubrics at 94%+ alignment with human markers — turning what took days into hours. Coaching institutes, consultancies and language schools run our full platform under their own brand, with AI writing and speaking evaluation, adaptive testing, psychometrics and a question bank across 12 standardized exams and 11 languages. PrepareBuddy is operated by Hyeontech Solutions Pvt. Ltd., a DPIIT-recognised startup, and is a member of the NVIDIA Inception programme and the AWS Education Equity Initiative.